RISK DRIVERS POSE TO THEMSELVES DUE TO TRAFFIC VIOLATIONS (original) (raw)
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Wyoming has one of the highest crash rates in the United States and a higher fatality rate than the U.S. average. These high rates result from many factors such as the high traffic through I-80 and the mountainous areas of Wyoming. This study employed two approaches to study contributory factors to crashes in the most hazardous interstate, I-80, in Wyoming by employing crash and citation data sets. Different factors may contribute to different driver actions so it is important to consider these crash causes separately. Thus, multiple logistic regression models were used in this study to examine the differences in crash-contributing factors for three driver actions: driving too fast for conditions, improper lane change, and no improper driving. These driver actions account for about 70% of all the crash causes on this interstate. The same violations as the two driver actions, improper lane change and driving too fast for conditions, account for 42% of all the crashes. The literature has indicated that previous violations can be used to predict future violations, and consequently crashes. Therefore, these violations were identified to detect the groups that are at higher risk of involvement in crashes. The analyses indicated that there are substantial differences across different driver actions for crash and violation data. For instance, not-dry-surface conditions increased the estimated odds of driving too fast for conditions 33 times while it decreased the risk of no improper driving by an estimated 250%. Crash severity, number of vehicles, vehicle maneuver, ‹ 36 › point of impact, driver condition, and speed compliance also impacted different driver actions differently. The results of violation analyses revealed that the interaction between types of vehicle and various variables were significant. For instance, nonresident truck drivers were more likely to violate all types of risky violations, which increased the estimated odds of crashes, compared with resident truck drivers. Recommendations based on the results are provided for policy makers to reduce high crash rate in the state.
Risk Perceptions of Drivers: Does It Change with Crash History or Prior Convictions?
This paper examines whether risk perceptions of drivers towards a traffic rule violation change with prior crash history or prior violations history. The data from the Naturalistic Driving Study (NDS), consisting of several surveys answered by voluntarily participated drivers across the United States, was used for research and analysis. The change in risk perception of participants is generally significant with involvement in two or more crashes. Participants between 16 to 19 years had a significant increase in the risk perception after involving in an injury severity crash. Participants between 16 to 19 years who were found at fault in a crash had significantly less risk perception than participants of the same age group who were not found at fault in a crash. Similarly, participants between 45 to 54 years had a significant change in the risk perceptions, but participants who were found at fault had high risk perceptions than who were not found at fault. Participants above 55 years and who were involved in injury severity crash found traffic rule violations less risky than participants of the same age group who were involved in damage only but not reported crashes. Overall, the results from this study help in understanding how drivers risk perceptions change after involving in crashes or convicted of violations. They assist in better educating drivers to increase the risk perceptions towards traffic rule violations so as to improve safety on roads.
The Relationship between Traffic Rule Violations and Accident Involvement Records of Drivers
2017
This paper aims to explore the relationship between the at-fault drivers involved in traffic accidents and their history of traffic violation records as a function of drivers' behavior. The employed data was integrated from different dataset systems in Abu Dhabi Traffic Police including traffic violations, accident information and drivers' licenses data systems. About 713,783 drivers involved in the analysis process with total accident number of 690,697 and total violation number of 2,762,011 during five years from 2010 to 2014. The analysis addressed two main parameters; accident rate per drivers and ratio of drivers with accident. Each parameter is investigated in terms of different variables; total number of violations, number of hazard violations, number of violations with penalty points and a cumulative number of traffic penalty points. The regression analysis shows a very strong relationship between the two parameters and the explanatory variables. In conclusion, the results indicated that the driver risk to be involved in future accidents can be predicted from prior driving records for traffic violations.
When dealing with the duality of mobility and safety, speed is one of the main factors causing deaths, so this is the reason why speed is one of the most studied topics related to road safety. The main objective of this research was to identify the aspects that modulate the speed-accidents relation. Specifically, the frequency and reasons why drivers speed. On the other hand, it was also considered the perception of drivers regarding the probability of penalty, the penalties imposed, and their severity. Finally, drivers' opinion on the effectiveness of such penalty in order to change speeding behavior was also studied. A sample of 1,100 Spanish drivers over 14 years old and having any kind of driving license was used. The results showed that approximately the third part of drivers always or sometimes sped. Among the specific reasons, the hurry, not having noticed, that the limits are too low or that the conditions allow doing so were the most frequent. Likewise, drivers considered as limited the probability of being caught. Finally, more than half of the drivers considered that the penalty they received was appropriate. Moreover, half of the drivers that received a penalty claimed that they changed their speeding habits as a result of such penalty. Drivers who speed are completely aware of the fact that they are breaking the traffic rules. Their speeding behavior is intentional in 80% of the cases. They are not aware of the risks of speeding since they justified their behavior by saying the speed limits are too low, the conditions on the roads allow doing so, or that it was a habit.
The relative frequency of unsafe driving acts in serious traffic crashes
2001
This study was conducted to determine the specific driver behaviors and unsafe driving acts (UDAS) that lead to crashes, and the situational, driver and vehicle characteristics associated with these behaviors. A sample of 723 crashes involving 1284 drivers was investigated from four different sites in the country during the period from April 1, 1996 through April 30, 1997. The crashes were selected using the National Automotive Sampling System (NASS) protocol and provide a fair sample of serious crashes involving passenger vehicles in the United States. In-depth data were collected and evaluated on the condition of the vehicles, the crash scene, roadway conditions, driver behaviors and situational factors at the time of the crash. Investigators used an 11 step process to evaluate the crash, determine the primary cause of each crash, and uncover contributing factors. Crash causes were attributed to either driver behavior or other causes. In 717 of the 723 crashes investigated (99%), a driver behavioral error caused or contributed to the crash. Of the 1284 drivers involved in these crashes, 732 drivers (57%) contributed in some way to the cause of their crashes. There were six causal factors associated with driver behaviors that occurred at relatively high frequencies for these drivers and accounted for most of the problem behaviors. They are: DRIVER INATTENTION-22.7%, VEHICLE SPEED-18.7%, ALCOHOL IMPAIRMENT-18.2%, PERCEPTUAL ERRORS (e.g. looked, but didn't see)-15.1%, DECISION ERRORS (e.g. turned with obstructed view)-10.1%, and INCAPACITATION (e.g. fell asleep)-6.4% Problem types in terms of crash configuration and specific problem behaviors were also identified. The following seven crash problem types accounted for almost half of the crashes studied where there was a driver behavioral error: SAME
PsycEXTRA Dataset, 2006
An assessment of the relative risk of engaging in potentially unsafe driving behaviors This report was funded by the AAA Foundation for Traffic Safety in Washington, D.C. Founded in 1947, the AAA Foundation is a not-for-profit, publicly supported charitable research and education organization dedicated to saving lives by preventing traffic crashes and reducing injuries when crashes occur. Funding for this report was provided by voluntary contributions from AAA/CAA and their affiliated motor clubs, from individual members, from AAA-affiliated insurance companies, as well as from other organizations or sources. This publication is distributed by the AAA Foundation for Traffic Safety at no charge, as a public service. It may not be resold or used for commercial purposes without the explicit permission of the Foundation. It may, however, be copied in whole or in part and distributed for free via any medium, provided the AAA Foundation is given appropriate credit as the source of the material. The opinions, findings, conclusions, and recommendations expressed in this publication are those of the authors and are not necessarily those of the AAA Foundation for Traffic Safety nor those of any individuals who peer-reviewed this report. The AAA Foundation for Traffic Safety assumes no liability for the use or misuse of any information, opinions, findings, conclusions, or recommendations contained in this report. If trade or manufacturer's names are mentioned, it is only because they are considered essential to the object of this report and their mention should not be construed as an endorsement. The AAA Foundation for Traffic Safety does not endorse products or manufacturers.
Major behavioral risk factors for road traffic injuries
One Health & Risk Management
Introduction. Road traffic injuries are a major public health problem, ranking 8th in the leading causes of death and are forecasted to rank 5th by 2030 worldwide. Children, pedestrians, cyclists and the elderly remain among those most at risk of road traffic injuries. Material and methods. A specialized literature search was conducted within the main international databases, including: PubMed/MEDLINE, Google Scholar, and Research Gate, using a set of inclusion criteria. Data from references were extracted systematically into results tables, including: author/citation, study design, assessments/data, limitations, and key facts. Reported outcomes were compiled in narrative form. Results. Many researchers and scientists both in the country and abroad have studied road injuries. Authors of the studies used different methods and obtained obvious data about road traumas and major risk factors. Among the main causes of unintentional motor vehicle injuries were excessive speed, alcohol con...
International Journal of Crashworthiness, 2019
The current study aims at examining the effect of aggressive driver behaviour, violation and error on motor vehicle crashes and investigating the factor structure of the Driver Behaviour Questionnaire (DBQ) factors on the crash involvement in Jordan. This is a cross-sectional study design conducted during September, 2016 to May 2017 in Amman, the capital of Jordan. The study included a representative sample of aged 22-65 years old 1450 drivers of which 1084 drivers agreed to participate (74.7%). The Manchester DBQ instrument was used to measure the aggressive, aberrant driving behaviours leading to crashes. Univariate and Multivariate logistic regression statistical analysis were performed. Out of a total 1084 responding drivers, 778 (71.7%) were males and 306 (28.3%) were females. The study revealed a statistically significant difference between males and females drivers in terms of age (p < 0.001), education (p < 0.001), occupation (p ¼ 046), marital status (p < 0.001), income (p < 0.001), driving experience (p < 0.001) and seat belts use (p < 0.001). Most of drivers admitted to ever had crashes (p < 0.001), careless driving (p < 0.001), having excessive speed (p < 0.001), smoking while driving (p < 0.001), crossing red traffic light (p < 0.001), using mobile phone (p < 0.001) and using SMS while driving (p ¼ 0.041). The DBQ mean scores of males were significantly higher in violations, error and frequently reported lapses whereas the mean driving skills score was similar between male and female divers. The factor included nine items of violations, six items of errors and five items of lapses in the Jordanian driver sample. Further, multivariate logistic regression analysis revealed violations, mobile phone use, excessive speed, driving skills, errors, lapses and type and size of vehicle significantly increased the risk of crash involvement. The results of the study demonstrated the increased risk of road traffic crashes among young Jordanian driverswhich had history of injuries at the time of crash (37.8%). Excessive speeding and mobile phone were the strongest predictors for the crash occurrence.
Journal of Transportation Technologies, 2014
Crash-prone drivers should be effectively targeted for various safety education and regulation programs because their over-involvement in crashes presents a big adverse effect on highway safety. By analyzing seven years of crash data from Louisiana, this paper investigates crash-prone drivers' characteristics and estimates their risk to have crashes in the seventh year based on these drivers' crash history of the past six years. The analysis results show that quite a few drivers repeatedly had crashes; seven drivers had 13 crashes in seven years; and the maximum number of crashes occurring in a single year to a single driver is eight. The probability of having crash(es) in any given year is closely related to a driver's crash history: less than 4% for drivers with no crash in the previous six years; and slightly higher than 30% for drivers with nine or more crashes in the previous six years. Based on the results, several suggestions are made on how to improve roadway safety through reducing crashes committed by drivers with much higher crash risk as identified by the analysis.